Efficiency Based Adaptive Local Refinement for First-Order System Least-Squares Formulations.

Adler, James H.
Manteuffel, Thomas Albert, 1948-
McCormick, S. F. (Stephen Fahrney), 1944-
Nolting, J.W.
Ruge, John.
Tang, L.

In this paper, we propose new adaptive local refinement (ALR) strategies for first-order system least-squares finite elements in conjunction with algebraic multigrid methods in the context of nested iteration. The goal is to reach a certain error tolerance with the least amount of computational cost and nearly uniform distribution of the error over all elements. To accomplish this, the refinement ... read more

Tufts University. Department of Mathematics.
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Original publication
J. H. Adler, T. Manteuffel, S. McCormick, J. Nolting, J. Ruge, and L. Tang. Efficiency-based adaptive local refinement for first-order system least-squares formulations. SIAM J. Sci. Comput. (SISC), 33(1):1-24, 2011. DOI:10.1137/100786897.
ID: tufts:22274
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